We will now start diving into Deep Q-Network (DQN) to train an agent to play GridWorld, which is a simple text-based game. There is a 4 x 4 grid of tiles and four objects are placed. There is an agent (a player), a pit, a goal, and a wall.
The project has the following structure:
- DeepQNetwork.java: Provides the reference architecture for the DQN
- Replay.java: Generates replay memory for the DQN to ensure that the gradients of the deep network are stable and do not diverge across episodes
- GridWorld.java: The main class used for training the DQN and playing the game. ...